{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "6b43fe78-b595-4607-88d2-89549de02791",
      "metadata": {
        "id": "6b43fe78-b595-4607-88d2-89549de02791",
        "outputId": "f4fa01ee-070a-42df-967d-08c4f420c870"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>subject_id</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>...</th>\n",
              "      <th>867</th>\n",
              "      <th>868</th>\n",
              "      <th>869</th>\n",
              "      <th>870</th>\n",
              "      <th>871</th>\n",
              "      <th>872</th>\n",
              "      <th>873</th>\n",
              "      <th>874</th>\n",
              "      <th>label_1</th>\n",
              "      <th>label_2</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>-0.502552</td>\n",
              "      <td>-0.532603</td>\n",
              "      <td>-0.562484</td>\n",
              "      <td>-0.591756</td>\n",
              "      <td>-0.620017</td>\n",
              "      <td>-0.646934</td>\n",
              "      <td>-0.672269</td>\n",
              "      <td>-0.695904</td>\n",
              "      <td>-0.717860</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.274259</td>\n",
              "      <td>-0.279373</td>\n",
              "      <td>-0.282512</td>\n",
              "      <td>-0.283788</td>\n",
              "      <td>-0.283321</td>\n",
              "      <td>-0.281237</td>\n",
              "      <td>-0.277671</td>\n",
              "      <td>-0.272755</td>\n",
              "      <td>98</td>\n",
              "      <td>57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>-0.324028</td>\n",
              "      <td>-0.367772</td>\n",
              "      <td>-0.411059</td>\n",
              "      <td>-0.453427</td>\n",
              "      <td>-0.494457</td>\n",
              "      <td>-0.533794</td>\n",
              "      <td>-0.571164</td>\n",
              "      <td>-0.606386</td>\n",
              "      <td>-0.639384</td>\n",
              "      <td>...</td>\n",
              "      <td>1.019408</td>\n",
              "      <td>0.970138</td>\n",
              "      <td>0.908652</td>\n",
              "      <td>0.835847</td>\n",
              "      <td>0.752798</td>\n",
              "      <td>0.660843</td>\n",
              "      <td>0.561622</td>\n",
              "      <td>0.457067</td>\n",
              "      <td>100</td>\n",
              "      <td>56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>0.078950</td>\n",
              "      <td>-0.023305</td>\n",
              "      <td>-0.123836</td>\n",
              "      <td>-0.221000</td>\n",
              "      <td>-0.313295</td>\n",
              "      <td>-0.399417</td>\n",
              "      <td>-0.478317</td>\n",
              "      <td>-0.549247</td>\n",
              "      <td>-0.611787</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.034969</td>\n",
              "      <td>-0.040990</td>\n",
              "      <td>-0.044514</td>\n",
              "      <td>-0.045987</td>\n",
              "      <td>-0.045662</td>\n",
              "      <td>-0.043620</td>\n",
              "      <td>-0.039810</td>\n",
              "      <td>-0.034107</td>\n",
              "      <td>115</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>0.233394</td>\n",
              "      <td>0.251590</td>\n",
              "      <td>0.267639</td>\n",
              "      <td>0.279521</td>\n",
              "      <td>0.285665</td>\n",
              "      <td>0.285092</td>\n",
              "      <td>0.277481</td>\n",
              "      <td>0.263138</td>\n",
              "      <td>0.242899</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.233065</td>\n",
              "      <td>-0.238201</td>\n",
              "      <td>-0.241181</td>\n",
              "      <td>-0.241780</td>\n",
              "      <td>-0.239970</td>\n",
              "      <td>-0.235934</td>\n",
              "      <td>-0.230042</td>\n",
              "      <td>-0.222807</td>\n",
              "      <td>83</td>\n",
              "      <td>55</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0</td>\n",
              "      <td>-0.173036</td>\n",
              "      <td>-0.190641</td>\n",
              "      <td>-0.208551</td>\n",
              "      <td>-0.226650</td>\n",
              "      <td>-0.244931</td>\n",
              "      <td>-0.263568</td>\n",
              "      <td>-0.282928</td>\n",
              "      <td>-0.303535</td>\n",
              "      <td>-0.325981</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.303961</td>\n",
              "      <td>-0.304851</td>\n",
              "      <td>-0.306394</td>\n",
              "      <td>-0.308315</td>\n",
              "      <td>-0.310368</td>\n",
              "      <td>-0.312341</td>\n",
              "      <td>-0.314045</td>\n",
              "      <td>-0.315297</td>\n",
              "      <td>109</td>\n",
              "      <td>58</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 878 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   subject_id         0         1         2         3         4         5  \\\n",
              "0           0 -0.502552 -0.532603 -0.562484 -0.591756 -0.620017 -0.646934   \n",
              "1           0 -0.324028 -0.367772 -0.411059 -0.453427 -0.494457 -0.533794   \n",
              "2           0  0.078950 -0.023305 -0.123836 -0.221000 -0.313295 -0.399417   \n",
              "3           0  0.233394  0.251590  0.267639  0.279521  0.285665  0.285092   \n",
              "4           0 -0.173036 -0.190641 -0.208551 -0.226650 -0.244931 -0.263568   \n",
              "\n",
              "          6         7         8  ...       867       868       869       870  \\\n",
              "0 -0.672269 -0.695904 -0.717860  ... -0.274259 -0.279373 -0.282512 -0.283788   \n",
              "1 -0.571164 -0.606386 -0.639384  ...  1.019408  0.970138  0.908652  0.835847   \n",
              "2 -0.478317 -0.549247 -0.611787  ... -0.034969 -0.040990 -0.044514 -0.045987   \n",
              "3  0.277481  0.263138  0.242899  ... -0.233065 -0.238201 -0.241181 -0.241780   \n",
              "4 -0.282928 -0.303535 -0.325981  ... -0.303961 -0.304851 -0.306394 -0.308315   \n",
              "\n",
              "        871       872       873       874  label_1  label_2  \n",
              "0 -0.283321 -0.281237 -0.277671 -0.272755       98       57  \n",
              "1  0.752798  0.660843  0.561622  0.457067      100       56  \n",
              "2 -0.045662 -0.043620 -0.039810 -0.034107      115       60  \n",
              "3 -0.239970 -0.235934 -0.230042 -0.222807       83       55  \n",
              "4 -0.310368 -0.312341 -0.314045 -0.315297      109       58  \n",
              "\n",
              "[5 rows x 878 columns]"
            ]
          },
          "execution_count": 1,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "df=pd.read_csv('file.csv')\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "0b9da824-e2bb-452c-b3ba-81ae90c2d870",
      "metadata": {
        "id": "0b9da824-e2bb-452c-b3ba-81ae90c2d870",
        "outputId": "4df33f59-8406-4f68-a1de-658cf9b6a8cc"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "              0         1         2         3         4         5         6  \\\n",
            "0     -0.502552 -0.532603 -0.562484 -0.591756 -0.620017 -0.646934 -0.672269   \n",
            "1     -0.324028 -0.367772 -0.411059 -0.453427 -0.494457 -0.533794 -0.571164   \n",
            "2      0.078950 -0.023305 -0.123836 -0.221000 -0.313295 -0.399417 -0.478317   \n",
            "3      0.233394  0.251590  0.267639  0.279521  0.285665  0.285092  0.277481   \n",
            "4     -0.173036 -0.190641 -0.208551 -0.226650 -0.244931 -0.263568 -0.282928   \n",
            "...         ...       ...       ...       ...       ...       ...       ...   \n",
            "99995 -0.291311 -0.331508 -0.372027 -0.413277 -0.455614 -0.499316 -0.544554   \n",
            "99996  0.284387  0.202390  0.123766  0.051923 -0.009643 -0.057388 -0.087826   \n",
            "99997  0.316428  0.384500  0.456288  0.534829  0.622359  0.720071  0.828020   \n",
            "99998 -0.428609 -0.467999 -0.508391 -0.550612 -0.595205 -0.642320 -0.691664   \n",
            "99999  0.320919  0.409317  0.501460  0.600375  0.708219  0.826024  0.953597   \n",
            "\n",
            "              7         8         9  ...       865       866       867  \\\n",
            "0     -0.695904 -0.717860 -0.738301  ... -0.257694 -0.267066 -0.274259   \n",
            "1     -0.606386 -0.639384 -0.670196  ...  1.077976  1.055641  1.019408   \n",
            "2     -0.549247 -0.611787 -0.665859  ... -0.012682 -0.025805 -0.034969   \n",
            "3      0.263138  0.242899  0.217966  ... -0.217937 -0.226153 -0.233065   \n",
            "4     -0.303535 -0.325981 -0.350782  ... -0.305273 -0.304013 -0.303961   \n",
            "...         ...       ...       ...  ...       ...       ...       ...   \n",
            "99995 -0.591374 -0.639693 -0.689289  ... -0.439221 -0.449205 -0.452549   \n",
            "99996 -0.097708 -0.084249 -0.045382  ... -0.312173 -0.319059 -0.322684   \n",
            "99997  0.945171  1.069563  1.198576  ... -0.133225 -0.151557 -0.168131   \n",
            "99998 -0.742502 -0.793726 -0.843979  ... -0.067754 -0.085605 -0.101980   \n",
            "99999  1.089575  1.231628  1.376749  ... -0.376388 -0.386156 -0.392286   \n",
            "\n",
            "            868       869       870       871       872       873       874  \n",
            "0     -0.279373 -0.282512 -0.283788 -0.283321 -0.281237 -0.277671 -0.272755  \n",
            "1      0.970138  0.908652  0.835847  0.752798  0.660843  0.561622  0.457067  \n",
            "2     -0.040990 -0.044514 -0.045987 -0.045662 -0.043620 -0.039810 -0.034107  \n",
            "3     -0.238201 -0.241181 -0.241780 -0.239970 -0.235934 -0.230042 -0.222807  \n",
            "4     -0.304851 -0.306394 -0.308315 -0.310368 -0.312341 -0.314045 -0.315297  \n",
            "...         ...       ...       ...       ...       ...       ...       ...  \n",
            "99995 -0.447246 -0.431814 -0.405569 -0.368806 -0.322865 -0.270047 -0.213388  \n",
            "99996 -0.323154 -0.320668 -0.315495 -0.307961 -0.298422 -0.287254 -0.274835  \n",
            "99997 -0.182824 -0.195521 -0.206152 -0.214715 -0.221279 -0.225981 -0.229005  \n",
            "99998 -0.116093 -0.127388 -0.135597 -0.140763 -0.143221 -0.143551 -0.142499  \n",
            "99999 -0.393486 -0.388743 -0.377508 -0.359829 -0.336406 -0.308551 -0.278049  \n",
            "\n",
            "[100000 rows x 875 columns]\n"
          ]
        }
      ],
      "source": [
        "subset_data = df.iloc[:, 1:-2]\n",
        "print(subset_data)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "43b5296d-6802-4229-a12f-18bd9bdbb15a",
      "metadata": {
        "id": "43b5296d-6802-4229-a12f-18bd9bdbb15a",
        "outputId": "b9fbb6fd-1872-4d6f-e766-35f6f02218d2"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>...</th>\n",
              "      <th>865</th>\n",
              "      <th>866</th>\n",
              "      <th>867</th>\n",
              "      <th>868</th>\n",
              "      <th>869</th>\n",
              "      <th>870</th>\n",
              "      <th>871</th>\n",
              "      <th>872</th>\n",
              "      <th>873</th>\n",
              "      <th>874</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-0.502552</td>\n",
              "      <td>-0.532603</td>\n",
              "      <td>-0.562484</td>\n",
              "      <td>-0.591756</td>\n",
              "      <td>-0.620017</td>\n",
              "      <td>-0.646934</td>\n",
              "      <td>-0.672269</td>\n",
              "      <td>-0.695904</td>\n",
              "      <td>-0.717860</td>\n",
              "      <td>-0.738301</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.257694</td>\n",
              "      <td>-0.267066</td>\n",
              "      <td>-0.274259</td>\n",
              "      <td>-0.279373</td>\n",
              "      <td>-0.282512</td>\n",
              "      <td>-0.283788</td>\n",
              "      <td>-0.283321</td>\n",
              "      <td>-0.281237</td>\n",
              "      <td>-0.277671</td>\n",
              "      <td>-0.272755</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.324028</td>\n",
              "      <td>-0.367772</td>\n",
              "      <td>-0.411059</td>\n",
              "      <td>-0.453427</td>\n",
              "      <td>-0.494457</td>\n",
              "      <td>-0.533794</td>\n",
              "      <td>-0.571164</td>\n",
              "      <td>-0.606386</td>\n",
              "      <td>-0.639384</td>\n",
              "      <td>-0.670196</td>\n",
              "      <td>...</td>\n",
              "      <td>1.077976</td>\n",
              "      <td>1.055641</td>\n",
              "      <td>1.019408</td>\n",
              "      <td>0.970138</td>\n",
              "      <td>0.908652</td>\n",
              "      <td>0.835847</td>\n",
              "      <td>0.752798</td>\n",
              "      <td>0.660843</td>\n",
              "      <td>0.561622</td>\n",
              "      <td>0.457067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.078950</td>\n",
              "      <td>-0.023305</td>\n",
              "      <td>-0.123836</td>\n",
              "      <td>-0.221000</td>\n",
              "      <td>-0.313295</td>\n",
              "      <td>-0.399417</td>\n",
              "      <td>-0.478317</td>\n",
              "      <td>-0.549247</td>\n",
              "      <td>-0.611787</td>\n",
              "      <td>-0.665859</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.012682</td>\n",
              "      <td>-0.025805</td>\n",
              "      <td>-0.034969</td>\n",
              "      <td>-0.040990</td>\n",
              "      <td>-0.044514</td>\n",
              "      <td>-0.045987</td>\n",
              "      <td>-0.045662</td>\n",
              "      <td>-0.043620</td>\n",
              "      <td>-0.039810</td>\n",
              "      <td>-0.034107</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.233394</td>\n",
              "      <td>0.251590</td>\n",
              "      <td>0.267639</td>\n",
              "      <td>0.279521</td>\n",
              "      <td>0.285665</td>\n",
              "      <td>0.285092</td>\n",
              "      <td>0.277481</td>\n",
              "      <td>0.263138</td>\n",
              "      <td>0.242899</td>\n",
              "      <td>0.217966</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.217937</td>\n",
              "      <td>-0.226153</td>\n",
              "      <td>-0.233065</td>\n",
              "      <td>-0.238201</td>\n",
              "      <td>-0.241181</td>\n",
              "      <td>-0.241780</td>\n",
              "      <td>-0.239970</td>\n",
              "      <td>-0.235934</td>\n",
              "      <td>-0.230042</td>\n",
              "      <td>-0.222807</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.173036</td>\n",
              "      <td>-0.190641</td>\n",
              "      <td>-0.208551</td>\n",
              "      <td>-0.226650</td>\n",
              "      <td>-0.244931</td>\n",
              "      <td>-0.263568</td>\n",
              "      <td>-0.282928</td>\n",
              "      <td>-0.303535</td>\n",
              "      <td>-0.325981</td>\n",
              "      <td>-0.350782</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.305273</td>\n",
              "      <td>-0.304013</td>\n",
              "      <td>-0.303961</td>\n",
              "      <td>-0.304851</td>\n",
              "      <td>-0.306394</td>\n",
              "      <td>-0.308315</td>\n",
              "      <td>-0.310368</td>\n",
              "      <td>-0.312341</td>\n",
              "      <td>-0.314045</td>\n",
              "      <td>-0.315297</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 875 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          0         1         2         3         4         5         6  \\\n",
              "0 -0.502552 -0.532603 -0.562484 -0.591756 -0.620017 -0.646934 -0.672269   \n",
              "1 -0.324028 -0.367772 -0.411059 -0.453427 -0.494457 -0.533794 -0.571164   \n",
              "2  0.078950 -0.023305 -0.123836 -0.221000 -0.313295 -0.399417 -0.478317   \n",
              "3  0.233394  0.251590  0.267639  0.279521  0.285665  0.285092  0.277481   \n",
              "4 -0.173036 -0.190641 -0.208551 -0.226650 -0.244931 -0.263568 -0.282928   \n",
              "\n",
              "          7         8         9  ...       865       866       867       868  \\\n",
              "0 -0.695904 -0.717860 -0.738301  ... -0.257694 -0.267066 -0.274259 -0.279373   \n",
              "1 -0.606386 -0.639384 -0.670196  ...  1.077976  1.055641  1.019408  0.970138   \n",
              "2 -0.549247 -0.611787 -0.665859  ... -0.012682 -0.025805 -0.034969 -0.040990   \n",
              "3  0.263138  0.242899  0.217966  ... -0.217937 -0.226153 -0.233065 -0.238201   \n",
              "4 -0.303535 -0.325981 -0.350782  ... -0.305273 -0.304013 -0.303961 -0.304851   \n",
              "\n",
              "        869       870       871       872       873       874  \n",
              "0 -0.282512 -0.283788 -0.283321 -0.281237 -0.277671 -0.272755  \n",
              "1  0.908652  0.835847  0.752798  0.660843  0.561622  0.457067  \n",
              "2 -0.044514 -0.045987 -0.045662 -0.043620 -0.039810 -0.034107  \n",
              "3 -0.241181 -0.241780 -0.239970 -0.235934 -0.230042 -0.222807  \n",
              "4 -0.306394 -0.308315 -0.310368 -0.312341 -0.314045 -0.315297  \n",
              "\n",
              "[5 rows x 875 columns]"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "subset_data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "94e4b850-f79d-4646-9d58-dbd3ca4935e6",
      "metadata": {
        "id": "94e4b850-f79d-4646-9d58-dbd3ca4935e6",
        "outputId": "c7fcfce5-f598-4bc0-b679-b844cac9e889"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "(100000, 875)\n"
          ]
        }
      ],
      "source": [
        "print(subset_data.shape)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "6e3871da-6954-4a80-b45d-406d649747a9",
      "metadata": {
        "id": "6e3871da-6954-4a80-b45d-406d649747a9",
        "outputId": "0174d6ba-dd8b-4d86-d2a8-f55251d15a22"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "          0         1         2         3         4         5         6  \\\n",
            "0 -0.502552 -0.532603 -0.562484 -0.591756 -0.620017 -0.646934 -0.672269   \n",
            "1 -0.324028 -0.367772 -0.411059 -0.453427 -0.494457 -0.533794 -0.571164   \n",
            "2  0.078950 -0.023305 -0.123836 -0.221000 -0.313295 -0.399417 -0.478317   \n",
            "3  0.233394  0.251590  0.267639  0.279521  0.285665  0.285092  0.277481   \n",
            "4 -0.173036 -0.190641 -0.208551 -0.226650 -0.244931 -0.263568 -0.282928   \n",
            "\n",
            "          7         8         9  ...       865       866       867       868  \\\n",
            "0 -0.695904 -0.717860 -0.738301  ... -0.257694 -0.267066 -0.274259 -0.279373   \n",
            "1 -0.606386 -0.639384 -0.670196  ...  1.077976  1.055641  1.019408  0.970138   \n",
            "2 -0.549247 -0.611787 -0.665859  ... -0.012682 -0.025805 -0.034969 -0.040990   \n",
            "3  0.263138  0.242899  0.217966  ... -0.217937 -0.226153 -0.233065 -0.238201   \n",
            "4 -0.303535 -0.325981 -0.350782  ... -0.305273 -0.304013 -0.303961 -0.304851   \n",
            "\n",
            "        869       870       871       872       873       874  \n",
            "0 -0.282512 -0.283788 -0.283321 -0.281237 -0.277671 -0.272755  \n",
            "1  0.908652  0.835847  0.752798  0.660843  0.561622  0.457067  \n",
            "2 -0.044514 -0.045987 -0.045662 -0.043620 -0.039810 -0.034107  \n",
            "3 -0.241181 -0.241780 -0.239970 -0.235934 -0.230042 -0.222807  \n",
            "4 -0.306394 -0.308315 -0.310368 -0.312341 -0.314045 -0.315297  \n",
            "\n",
            "[5 rows x 875 columns]\n",
            "(100000, 875)\n"
          ]
        }
      ],
      "source": [
        "reloaded_data = pd.read_csv(\"subset_data.csv\")\n",
        "print(reloaded_data.head())\n",
        "print(reloaded_data.shape)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "12f50d8b-fc85-4ba4-8693-b4d654e15d2c",
      "metadata": {
        "id": "12f50d8b-fc85-4ba4-8693-b4d654e15d2c",
        "outputId": "d1c005d6-c81a-4016-f131-9d784785889c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: pywavelets in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (1.7.0)\n",
            "Requirement already satisfied: numpy<3,>=1.23 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from pywavelets) (1.26.4)\n"
          ]
        }
      ],
      "source": [
        "!pip install pywavelets\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ff0a30c3-44a6-4b8d-926b-35ccd7f9885d",
      "metadata": {
        "id": "ff0a30c3-44a6-4b8d-926b-35ccd7f9885d",
        "outputId": "684380ad-9dd9-49ec-a4a8-103679f9a94f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "          0         1         2         3         4         5         6  \\\n",
            "0 -0.502552 -0.532603 -0.562484 -0.591756 -0.620017 -0.646934 -0.672269   \n",
            "1 -0.324028 -0.367772 -0.411059 -0.453427 -0.494457 -0.533794 -0.571164   \n",
            "2  0.078950 -0.023305 -0.123836 -0.221000 -0.313295 -0.399417 -0.478317   \n",
            "3  0.233394  0.251590  0.267639  0.279521  0.285665  0.285092  0.277481   \n",
            "4 -0.173036 -0.190641 -0.208551 -0.226650 -0.244931 -0.263568 -0.282928   \n",
            "\n",
            "          7         8         9  ...       865       866       867       868  \\\n",
            "0 -0.695904 -0.717860 -0.738301  ... -0.257694 -0.267066 -0.274259 -0.279373   \n",
            "1 -0.606386 -0.639384 -0.670196  ...  1.077976  1.055641  1.019408  0.970138   \n",
            "2 -0.549247 -0.611787 -0.665859  ... -0.012682 -0.025805 -0.034969 -0.040990   \n",
            "3  0.263138  0.242899  0.217966  ... -0.217937 -0.226153 -0.233065 -0.238201   \n",
            "4 -0.303535 -0.325981 -0.350782  ... -0.305273 -0.304013 -0.303961 -0.304851   \n",
            "\n",
            "        869       870       871       872       873       874  \n",
            "0 -0.282512 -0.283788 -0.283321 -0.281237 -0.277671 -0.272755  \n",
            "1  0.908652  0.835847  0.752798  0.660843  0.561622  0.457067  \n",
            "2 -0.044514 -0.045987 -0.045662 -0.043620 -0.039810 -0.034107  \n",
            "3 -0.241181 -0.241780 -0.239970 -0.235934 -0.230042 -0.222807  \n",
            "4 -0.306394 -0.308315 -0.310368 -0.312341 -0.314045 -0.315297  \n",
            "\n",
            "[5 rows x 875 columns]\n",
            "(100000, 875)\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1000x600 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Denoised data has been written to 'denoised_subset_data.csv'\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import pywt\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Load the dataset\n",
        "reloaded_data = pd.read_csv(\"subset_data.csv\")\n",
        "print(reloaded_data.head())\n",
        "print(reloaded_data.shape)\n",
        "\n",
        "# Function to apply DWT (Discrete Wavelet Transform) for noise reduction\n",
        "def apply_wavelet_on_row(signal):\n",
        "    # Apply DWT (you can choose the wavelet and level)\n",
        "    coeffs = pywt.wavedec(signal, 'db4', level=5)  # db4 is Daubechies wavelet\n",
        "\n",
        "    # Thresholding the coefficients for noise removal (example threshold)\n",
        "    thresholded_coeffs = [np.where(np.abs(coeff) > 0.05, coeff, 0) for coeff in coeffs]\n",
        "\n",
        "    # Reconstruct the signal from thresholded coefficients\n",
        "    denoised_signal = pywt.waverec(thresholded_coeffs, 'db4')\n",
        "\n",
        "    return denoised_signal\n",
        "\n",
        "# Plotting function for comparison\n",
        "def plot_comparison(original_signal, denoised_signal, index=0):\n",
        "    plt.figure(figsize=(10, 6))\n",
        "    plt.subplot(2, 1, 1)\n",
        "    plt.plot(original_signal, label=\"Original Signal\")\n",
        "    plt.title(f\"Original Signal - Row {index}\")\n",
        "    plt.legend()\n",
        "\n",
        "    plt.subplot(2, 1, 2)\n",
        "    plt.plot(denoised_signal, label=\"Denoised Signal\", color='orange')\n",
        "    plt.title(f\"Denoised Signal - Row {index}\")\n",
        "    plt.legend()\n",
        "\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "# Apply DWT to a sample row (you can choose any row from your dataset)\n",
        "sample_index = 0  # Change this index to visualize other rows\n",
        "sample_row = reloaded_data.iloc[sample_index]\n",
        "\n",
        "# Apply wavelet denoising\n",
        "denoised_sample = apply_wavelet_on_row(sample_row)\n",
        "\n",
        "# Plot the original and denoised signals\n",
        "plot_comparison(sample_row, denoised_sample, sample_index)\n",
        "\n",
        "# Apply DWT to all rows and store the denoised signals (optional)\n",
        "denoised_data = []\n",
        "for index, row in reloaded_data.iterrows():\n",
        "    signal = row.to_numpy()\n",
        "    denoised_signal = apply_wavelet_on_row(signal)\n",
        "    denoised_data.append(denoised_signal[:len(signal)])  # Trim to the original length if needed\n",
        "\n",
        "# Convert denoised data to DataFrame\n",
        "denoised_df = pd.DataFrame(denoised_data, columns=reloaded_data.columns)\n",
        "\n",
        "# Save the denoised dataset\n",
        "denoised_df.to_csv(\"denoised_subset_data.csv\", index=False)\n",
        "print(\"Denoised data has been written to 'denoised_subset_data.csv'\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "471fc644-6c74-444f-8bde-6f32da76260d",
      "metadata": {
        "scrolled": true,
        "id": "471fc644-6c74-444f-8bde-6f32da76260d",
        "outputId": "68f0bb31-828e-46c8-bba0-3c50ea8d61ea"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Difference in Row 1 values:\n",
            "0      0.010246\n",
            "1      0.025918\n",
            "2      0.015356\n",
            "3     -0.015924\n",
            "4     -0.010271\n",
            "         ...   \n",
            "870   -0.000327\n",
            "871   -0.000198\n",
            "872    0.000324\n",
            "873    0.001982\n",
            "874   -0.033931\n",
            "Name: 1, Length: 875, dtype: float64\n"
          ]
        }
      ],
      "source": [
        "# Load the original and denoised datasets\n",
        "original_data = pd.read_csv(\"subset_data.csv\")\n",
        "denoised_data = pd.read_csv(\"denoised_subset_data.csv\")\n",
        "\n",
        "# Get Row 1 of each dataset (index 1)\n",
        "original_row_1 = original_data.iloc[1]\n",
        "denoised_row_1 = denoised_data.iloc[1]\n",
        "\n",
        "# Calculate the difference\n",
        "difference_row_1 = original_row_1 - denoised_row_1\n",
        "print(\"Difference in Row 1 values:\")\n",
        "print(difference_row_1)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a3de00a8-962a-4aa7-9912-d0cb3e3a5a8a",
      "metadata": {
        "id": "a3de00a8-962a-4aa7-9912-d0cb3e3a5a8a",
        "outputId": "25b08110-bd52-496e-85fc-0a32632ab82e"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>...</th>\n",
              "      <th>865</th>\n",
              "      <th>866</th>\n",
              "      <th>867</th>\n",
              "      <th>868</th>\n",
              "      <th>869</th>\n",
              "      <th>870</th>\n",
              "      <th>871</th>\n",
              "      <th>872</th>\n",
              "      <th>873</th>\n",
              "      <th>874</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-0.530895</td>\n",
              "      <td>-0.547640</td>\n",
              "      <td>-0.567601</td>\n",
              "      <td>-0.587911</td>\n",
              "      <td>-0.622097</td>\n",
              "      <td>-0.668470</td>\n",
              "      <td>-0.699408</td>\n",
              "      <td>-0.714772</td>\n",
              "      <td>-0.726910</td>\n",
              "      <td>-0.729182</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.258364</td>\n",
              "      <td>-0.267032</td>\n",
              "      <td>-0.272963</td>\n",
              "      <td>-0.276157</td>\n",
              "      <td>-0.276627</td>\n",
              "      <td>-0.277585</td>\n",
              "      <td>-0.279357</td>\n",
              "      <td>-0.280418</td>\n",
              "      <td>-0.281699</td>\n",
              "      <td>-0.281236</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.334274</td>\n",
              "      <td>-0.393691</td>\n",
              "      <td>-0.426415</td>\n",
              "      <td>-0.437503</td>\n",
              "      <td>-0.484185</td>\n",
              "      <td>-0.554313</td>\n",
              "      <td>-0.598714</td>\n",
              "      <td>-0.621698</td>\n",
              "      <td>-0.641376</td>\n",
              "      <td>-0.647708</td>\n",
              "      <td>...</td>\n",
              "      <td>1.075485</td>\n",
              "      <td>1.052333</td>\n",
              "      <td>1.018969</td>\n",
              "      <td>0.970151</td>\n",
              "      <td>0.908639</td>\n",
              "      <td>0.836174</td>\n",
              "      <td>0.752996</td>\n",
              "      <td>0.660519</td>\n",
              "      <td>0.559640</td>\n",
              "      <td>0.490998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.075141</td>\n",
              "      <td>-0.032244</td>\n",
              "      <td>-0.123945</td>\n",
              "      <td>-0.217764</td>\n",
              "      <td>-0.312205</td>\n",
              "      <td>-0.383845</td>\n",
              "      <td>-0.471975</td>\n",
              "      <td>-0.567682</td>\n",
              "      <td>-0.629008</td>\n",
              "      <td>-0.656504</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.009959</td>\n",
              "      <td>-0.020149</td>\n",
              "      <td>-0.032561</td>\n",
              "      <td>-0.038546</td>\n",
              "      <td>-0.041447</td>\n",
              "      <td>-0.042842</td>\n",
              "      <td>-0.042409</td>\n",
              "      <td>-0.042170</td>\n",
              "      <td>-0.042745</td>\n",
              "      <td>-0.041622</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.258271</td>\n",
              "      <td>0.269103</td>\n",
              "      <td>0.274880</td>\n",
              "      <td>0.273692</td>\n",
              "      <td>0.274553</td>\n",
              "      <td>0.274750</td>\n",
              "      <td>0.269284</td>\n",
              "      <td>0.258535</td>\n",
              "      <td>0.242656</td>\n",
              "      <td>0.220352</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.211742</td>\n",
              "      <td>-0.217059</td>\n",
              "      <td>-0.220786</td>\n",
              "      <td>-0.224290</td>\n",
              "      <td>-0.227266</td>\n",
              "      <td>-0.229446</td>\n",
              "      <td>-0.231004</td>\n",
              "      <td>-0.231891</td>\n",
              "      <td>-0.232113</td>\n",
              "      <td>-0.232196</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.190365</td>\n",
              "      <td>-0.213571</td>\n",
              "      <td>-0.229571</td>\n",
              "      <td>-0.235408</td>\n",
              "      <td>-0.247355</td>\n",
              "      <td>-0.260757</td>\n",
              "      <td>-0.277343</td>\n",
              "      <td>-0.299070</td>\n",
              "      <td>-0.321555</td>\n",
              "      <td>-0.345734</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.299022</td>\n",
              "      <td>-0.296311</td>\n",
              "      <td>-0.298058</td>\n",
              "      <td>-0.304561</td>\n",
              "      <td>-0.316908</td>\n",
              "      <td>-0.321526</td>\n",
              "      <td>-0.317786</td>\n",
              "      <td>-0.313579</td>\n",
              "      <td>-0.305595</td>\n",
              "      <td>-0.303165</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 875 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          0         1         2         3         4         5         6  \\\n",
              "0 -0.530895 -0.547640 -0.567601 -0.587911 -0.622097 -0.668470 -0.699408   \n",
              "1 -0.334274 -0.393691 -0.426415 -0.437503 -0.484185 -0.554313 -0.598714   \n",
              "2  0.075141 -0.032244 -0.123945 -0.217764 -0.312205 -0.383845 -0.471975   \n",
              "3  0.258271  0.269103  0.274880  0.273692  0.274553  0.274750  0.269284   \n",
              "4 -0.190365 -0.213571 -0.229571 -0.235408 -0.247355 -0.260757 -0.277343   \n",
              "\n",
              "          7         8         9  ...       865       866       867       868  \\\n",
              "0 -0.714772 -0.726910 -0.729182  ... -0.258364 -0.267032 -0.272963 -0.276157   \n",
              "1 -0.621698 -0.641376 -0.647708  ...  1.075485  1.052333  1.018969  0.970151   \n",
              "2 -0.567682 -0.629008 -0.656504  ... -0.009959 -0.020149 -0.032561 -0.038546   \n",
              "3  0.258535  0.242656  0.220352  ... -0.211742 -0.217059 -0.220786 -0.224290   \n",
              "4 -0.299070 -0.321555 -0.345734  ... -0.299022 -0.296311 -0.298058 -0.304561   \n",
              "\n",
              "        869       870       871       872       873       874  \n",
              "0 -0.276627 -0.277585 -0.279357 -0.280418 -0.281699 -0.281236  \n",
              "1  0.908639  0.836174  0.752996  0.660519  0.559640  0.490998  \n",
              "2 -0.041447 -0.042842 -0.042409 -0.042170 -0.042745 -0.041622  \n",
              "3 -0.227266 -0.229446 -0.231004 -0.231891 -0.232113 -0.232196  \n",
              "4 -0.316908 -0.321526 -0.317786 -0.313579 -0.305595 -0.303165  \n",
              "\n",
              "[5 rows x 875 columns]"
            ]
          },
          "execution_count": 63,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "denoised_data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "3dbbb43b-2c56-4023-ae46-aa01bbad4d14",
      "metadata": {
        "id": "3dbbb43b-2c56-4023-ae46-aa01bbad4d14",
        "outputId": "84969232-5297-4bad-bd60-029e03ac5ea9"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "      <th>7</th>\n",
              "      <th>8</th>\n",
              "      <th>9</th>\n",
              "      <th>...</th>\n",
              "      <th>865</th>\n",
              "      <th>866</th>\n",
              "      <th>867</th>\n",
              "      <th>868</th>\n",
              "      <th>869</th>\n",
              "      <th>870</th>\n",
              "      <th>871</th>\n",
              "      <th>872</th>\n",
              "      <th>873</th>\n",
              "      <th>874</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-0.502552</td>\n",
              "      <td>-0.532603</td>\n",
              "      <td>-0.562484</td>\n",
              "      <td>-0.591756</td>\n",
              "      <td>-0.620017</td>\n",
              "      <td>-0.646934</td>\n",
              "      <td>-0.672269</td>\n",
              "      <td>-0.695904</td>\n",
              "      <td>-0.717860</td>\n",
              "      <td>-0.738301</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.257694</td>\n",
              "      <td>-0.267066</td>\n",
              "      <td>-0.274259</td>\n",
              "      <td>-0.279373</td>\n",
              "      <td>-0.282512</td>\n",
              "      <td>-0.283788</td>\n",
              "      <td>-0.283321</td>\n",
              "      <td>-0.281237</td>\n",
              "      <td>-0.277671</td>\n",
              "      <td>-0.272755</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.324028</td>\n",
              "      <td>-0.367772</td>\n",
              "      <td>-0.411059</td>\n",
              "      <td>-0.453427</td>\n",
              "      <td>-0.494457</td>\n",
              "      <td>-0.533794</td>\n",
              "      <td>-0.571164</td>\n",
              "      <td>-0.606386</td>\n",
              "      <td>-0.639384</td>\n",
              "      <td>-0.670196</td>\n",
              "      <td>...</td>\n",
              "      <td>1.077976</td>\n",
              "      <td>1.055641</td>\n",
              "      <td>1.019408</td>\n",
              "      <td>0.970138</td>\n",
              "      <td>0.908652</td>\n",
              "      <td>0.835847</td>\n",
              "      <td>0.752798</td>\n",
              "      <td>0.660843</td>\n",
              "      <td>0.561622</td>\n",
              "      <td>0.457067</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.078950</td>\n",
              "      <td>-0.023305</td>\n",
              "      <td>-0.123836</td>\n",
              "      <td>-0.221000</td>\n",
              "      <td>-0.313295</td>\n",
              "      <td>-0.399417</td>\n",
              "      <td>-0.478317</td>\n",
              "      <td>-0.549247</td>\n",
              "      <td>-0.611787</td>\n",
              "      <td>-0.665859</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.012682</td>\n",
              "      <td>-0.025805</td>\n",
              "      <td>-0.034969</td>\n",
              "      <td>-0.040990</td>\n",
              "      <td>-0.044514</td>\n",
              "      <td>-0.045987</td>\n",
              "      <td>-0.045662</td>\n",
              "      <td>-0.043620</td>\n",
              "      <td>-0.039810</td>\n",
              "      <td>-0.034107</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.233394</td>\n",
              "      <td>0.251590</td>\n",
              "      <td>0.267639</td>\n",
              "      <td>0.279521</td>\n",
              "      <td>0.285665</td>\n",
              "      <td>0.285092</td>\n",
              "      <td>0.277481</td>\n",
              "      <td>0.263138</td>\n",
              "      <td>0.242899</td>\n",
              "      <td>0.217966</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.217937</td>\n",
              "      <td>-0.226153</td>\n",
              "      <td>-0.233065</td>\n",
              "      <td>-0.238201</td>\n",
              "      <td>-0.241181</td>\n",
              "      <td>-0.241780</td>\n",
              "      <td>-0.239970</td>\n",
              "      <td>-0.235934</td>\n",
              "      <td>-0.230042</td>\n",
              "      <td>-0.222807</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.173036</td>\n",
              "      <td>-0.190641</td>\n",
              "      <td>-0.208551</td>\n",
              "      <td>-0.226650</td>\n",
              "      <td>-0.244931</td>\n",
              "      <td>-0.263568</td>\n",
              "      <td>-0.282928</td>\n",
              "      <td>-0.303535</td>\n",
              "      <td>-0.325981</td>\n",
              "      <td>-0.350782</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.305273</td>\n",
              "      <td>-0.304013</td>\n",
              "      <td>-0.303961</td>\n",
              "      <td>-0.304851</td>\n",
              "      <td>-0.306394</td>\n",
              "      <td>-0.308315</td>\n",
              "      <td>-0.310368</td>\n",
              "      <td>-0.312341</td>\n",
              "      <td>-0.314045</td>\n",
              "      <td>-0.315297</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 875 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          0         1         2         3         4         5         6  \\\n",
              "0 -0.502552 -0.532603 -0.562484 -0.591756 -0.620017 -0.646934 -0.672269   \n",
              "1 -0.324028 -0.367772 -0.411059 -0.453427 -0.494457 -0.533794 -0.571164   \n",
              "2  0.078950 -0.023305 -0.123836 -0.221000 -0.313295 -0.399417 -0.478317   \n",
              "3  0.233394  0.251590  0.267639  0.279521  0.285665  0.285092  0.277481   \n",
              "4 -0.173036 -0.190641 -0.208551 -0.226650 -0.244931 -0.263568 -0.282928   \n",
              "\n",
              "          7         8         9  ...       865       866       867       868  \\\n",
              "0 -0.695904 -0.717860 -0.738301  ... -0.257694 -0.267066 -0.274259 -0.279373   \n",
              "1 -0.606386 -0.639384 -0.670196  ...  1.077976  1.055641  1.019408  0.970138   \n",
              "2 -0.549247 -0.611787 -0.665859  ... -0.012682 -0.025805 -0.034969 -0.040990   \n",
              "3  0.263138  0.242899  0.217966  ... -0.217937 -0.226153 -0.233065 -0.238201   \n",
              "4 -0.303535 -0.325981 -0.350782  ... -0.305273 -0.304013 -0.303961 -0.304851   \n",
              "\n",
              "        869       870       871       872       873       874  \n",
              "0 -0.282512 -0.283788 -0.283321 -0.281237 -0.277671 -0.272755  \n",
              "1  0.908652  0.835847  0.752798  0.660843  0.561622  0.457067  \n",
              "2 -0.044514 -0.045987 -0.045662 -0.043620 -0.039810 -0.034107  \n",
              "3 -0.241181 -0.241780 -0.239970 -0.235934 -0.230042 -0.222807  \n",
              "4 -0.306394 -0.308315 -0.310368 -0.312341 -0.314045 -0.315297  \n",
              "\n",
              "[5 rows x 875 columns]"
            ]
          },
          "execution_count": 64,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "original_data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "003ce652-3921-469d-87fe-b27a140e07fe",
      "metadata": {
        "id": "003ce652-3921-469d-87fe-b27a140e07fe"
      },
      "outputs": [],
      "source": [
        "#denoised_df = reloaded_data.apply(lambda row: apply_wavelet_on_row(row.to_numpy()), axis=1, result_type=\"expand\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "f5ca7719-8f43-41c1-b1fd-278bc5e25a06",
      "metadata": {
        "id": "f5ca7719-8f43-41c1-b1fd-278bc5e25a06"
      },
      "source": [
        "# plot before after normalised the signal"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "01c0d981-2059-483f-b8d1-b5abbc951725",
      "metadata": {
        "id": "01c0d981-2059-483f-b8d1-b5abbc951725",
        "outputId": "ef86f7b9-1924-42bb-a404-8ff6afd6013b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "          0         1         2         3         4         5         6  \\\n",
            "0  0.320597  0.286392  0.276152  0.285881  0.316446  0.333954  0.350685   \n",
            "1  0.378363  0.338413  0.321534  0.321136  0.343270  0.354545  0.366964   \n",
            "2  0.508757  0.447129  0.407613  0.380374  0.381973  0.379001  0.381914   \n",
            "3  0.558732  0.533887  0.524936  0.507939  0.509932  0.503579  0.503610   \n",
            "4  0.427221  0.394317  0.382224  0.378934  0.396578  0.403725  0.413375   \n",
            "\n",
            "          7         8         9  ...       865       866       867       868  \\\n",
            "0  0.367491  0.384722  0.392311  ...  0.470269  0.465172  0.462682  0.461631   \n",
            "1  0.380630  0.395486  0.401007  ...  0.596828  0.592441  0.592612  0.596691   \n",
            "2  0.389016  0.399271  0.401561  ...  0.493484  0.488386  0.486715  0.487398   \n",
            "3  0.508255  0.516506  0.514412  ...  0.474036  0.469108  0.466819  0.466082   \n",
            "4  0.425081  0.438475  0.441792  ...  0.465760  0.461617  0.459699  0.458878   \n",
            "\n",
            "        869       870       871       872       873       874  \n",
            "0  0.460870  0.459110  0.454564  0.443794  0.373485  0.364558  \n",
            "1  0.604429  0.616268  0.634144  0.664102  0.653482  0.647596  \n",
            "2  0.489554  0.492489  0.495755  0.499362  0.452838  0.457110  \n",
            "3  0.465852  0.465007  0.462078  0.454389  0.389374  0.383929  \n",
            "4  0.457992  0.455668  0.449876  0.436521  0.361350  0.348060  \n",
            "\n",
            "[5 rows x 875 columns]\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1200x600 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Load the dataset\n",
        "subset_data = pd.read_csv(\"subset_data.csv\")\n",
        "\n",
        "# Apply Min-Max normalization (from the original code you provided)\n",
        "subset_data_normalized = subset_data.apply(lambda x: (x - x.min()) / (x.max() - x.min()), axis=0)\n",
        "\n",
        "# Print the first few rows of the normalized data\n",
        "print(subset_data_normalized.head())\n",
        "\n",
        "# Plotting the comparison of the original and normalized data\n",
        "# Choose a specific row (signal) to visualize, for example, the first row\n",
        "row_index = 0  # Change this index to visualize other rows\n",
        "\n",
        "# Extract the original and normalized signal for this row\n",
        "original_signal = subset_data.iloc[row_index, :-2]  # Exclude the last two label columns\n",
        "normalized_signal = subset_data_normalized.iloc[row_index, :-2]  # Exclude the last two label columns\n",
        "\n",
        "# Create the plot\n",
        "plt.figure(figsize=(12, 6))\n",
        "\n",
        "# Plot original signal\n",
        "plt.subplot(2, 1, 1)\n",
        "plt.plot(original_signal, label=\"Original Signal\", color=\"blue\")\n",
        "plt.title(f\"Original Signal - Row {row_index}\")\n",
        "plt.xlabel(\"Time (seconds)\")\n",
        "plt.ylabel(\"Signal Amplitude\")\n",
        "plt.legend()\n",
        "\n",
        "# Plot normalized signal\n",
        "plt.subplot(2, 1, 2)\n",
        "plt.plot(normalized_signal, label=\"Normalized Signal\", color=\"orange\")\n",
        "plt.title(f\"Normalized Signal - Row {row_index}\")\n",
        "plt.xlabel(\"Time (seconds)\")\n",
        "plt.ylabel(\"Normalized Amplitude\")\n",
        "plt.legend()\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "004b8f03-3b82-4229-8d47-4f195dba1f11",
      "metadata": {
        "id": "004b8f03-3b82-4229-8d47-4f195dba1f11"
      },
      "outputs": [],
      "source": [
        "subset_data_normalized.to_csv('subset_data_normalized.csv', index=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "31416550-6a91-4876-b039-b65a1d07e26a",
      "metadata": {
        "id": "31416550-6a91-4876-b039-b65a1d07e26a"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "19ab1a9d-ed02-4441-a61d-eb05e991b8b4",
      "metadata": {
        "id": "19ab1a9d-ed02-4441-a61d-eb05e991b8b4",
        "outputId": "8c562c7f-8cb2-4e96-f600-0f73026bc303"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: EMD-signal in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (1.6.4)\n",
            "Requirement already satisfied: numpy>=1.12 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from EMD-signal) (1.26.4)\n",
            "Requirement already satisfied: scipy>=0.19 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from EMD-signal) (1.13.1)\n",
            "Requirement already satisfied: pathos>=0.2.1 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from EMD-signal) (0.3.3)\n",
            "Requirement already satisfied: tqdm<5.0,>=4.64.0 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from EMD-signal) (4.66.5)\n",
            "Requirement already satisfied: ppft>=1.7.6.9 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from pathos>=0.2.1->EMD-signal) (1.7.6.9)\n",
            "Requirement already satisfied: dill>=0.3.9 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from pathos>=0.2.1->EMD-signal) (0.3.9)\n",
            "Requirement already satisfied: pox>=0.3.5 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from pathos>=0.2.1->EMD-signal) (0.3.5)\n",
            "Requirement already satisfied: multiprocess>=0.70.17 in c:\\users\\iiit-nr\\anaconda3\\lib\\site-packages (from pathos>=0.2.1->EMD-signal) (0.70.17)\n",
            "Requirement already satisfied: colorama in c:\\users\\iiit-nr\\appdata\\roaming\\python\\python312\\site-packages (from tqdm<5.0,>=4.64.0->EMD-signal) (0.4.6)\n"
          ]
        }
      ],
      "source": [
        "!pip install EMD-signal\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "d252091c-00b9-42e9-b008-82380c802d3f",
      "metadata": {
        "id": "d252091c-00b9-42e9-b008-82380c802d3f",
        "outputId": "610aa801-c51d-420e-cec3-a5f2c662632f"
      },
      "outputs": [
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from scipy.signal import find_peaks\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Assuming `subset_data_normalized` is already loaded\n",
        "ppg_signal = subset_data_normalized.iloc[0, :-2].values  # Use only the signal columns, exclude labels\n",
        "\n",
        "# Step 1: Normalize the PPG waveform to range 0-1 for amplitude\n",
        "min_val = np.min(ppg_signal)\n",
        "max_val = np.max(ppg_signal)\n",
        "ppg_signal_normalized = -1 + 2 * (ppg_signal - min_val) / (max_val - min_val)\n",
        "\n",
        "# Step 2: Align the time axis to range from 0 to 1 (normalize x-axis as well)\n",
        "time_axis = np.linspace(0, 1, len(ppg_signal_normalized))\n",
        "\n",
        "# Step 3: Detect peaks on the normalized signal\n",
        "systolic_peaks, _ = find_peaks(ppg_signal_normalized, height=0.6, distance=30)\n",
        "diastolic_peaks, _ = find_peaks(-ppg_signal_normalized, height=-0.3, distance=30)\n",
        "\n",
        "# Detect dicrotic notch (minimum between systolic peaks)\n",
        "dicrotic_notches = []\n",
        "for i in range(len(systolic_peaks) - 1):\n",
        "    start, end = systolic_peaks[i], systolic_peaks[i + 1]\n",
        "    if start < end:\n",
        "        dicrotic_notch = np.argmin(ppg_signal_normalized[start:end]) + start\n",
        "        dicrotic_notches.append(dicrotic_notch)\n",
        "\n",
        "# Step 4: Plot with annotations\n",
        "\n",
        "plt.figure(figsize=(12, 6))\n",
        "plt.plot(time_axis, ppg_signal_normalized, label=\"Normalized PPG Signal\", color='purple')\n",
        "plt.axhline(0, color='brown', linestyle='--', linewidth=2, label=\"x=0 Line\")\n",
        "\n",
        "\n",
        "# Mark Systolic Peaks\n",
        "plt.plot(time_axis[systolic_peaks], ppg_signal_normalized[systolic_peaks], \"ro\", label=\"Systolic Peaks\")\n",
        "\n",
        "# Mark Diastolic Peaks\n",
        "plt.plot(time_axis[diastolic_peaks], ppg_signal_normalized[diastolic_peaks], \"go\", label=\"Diastolic Peaks\")\n",
        "\n",
        "# Mark Dicrotic Notches\n",
        "plt.plot(time_axis[dicrotic_notches], ppg_signal_normalized[dicrotic_notches], \"bo\", label=\"Dicrotic Notches\")\n",
        "\n",
        "# Add annotations for each detected feature\n",
        "for peak in systolic_peaks:\n",
        "    plt.annotate(\"Systolic Peak\", (time_axis[peak], ppg_signal_normalized[peak]),\n",
        "                 textcoords=\"offset points\", xytext=(0,10), ha='center', color='red')\n",
        "\n",
        "for peak in diastolic_peaks:\n",
        "    plt.annotate(\"Diastolic Peak\", (time_axis[peak], ppg_signal_normalized[peak]),\n",
        "                 textcoords=\"offset points\", xytext=(0,10), ha='center', color='green')\n",
        "\n",
        "for notch in dicrotic_notches:\n",
        "    plt.annotate(\"Dicrotic Notch\", (time_axis[notch], ppg_signal_normalized[notch]),\n",
        "                 textcoords=\"offset points\", xytext=(0,-15), ha='center', color='blue')\n",
        "\n",
        "# Amplitude Difference (Augmentation)\n",
        "if len(systolic_peaks) > 0 and len(diastolic_peaks) > 0:\n",
        "    amplitude_diff = ppg_signal_normalized[systolic_peaks[0]] - ppg_signal_normalized[diastolic_peaks[0]]\n",
        "    plt.annotate('', xy=(time_axis[systolic_peaks[0]], ppg_signal_normalized[systolic_peaks[0]]),\n",
        "                 xytext=(time_axis[diastolic_peaks[0]], ppg_signal_normalized[diastolic_peaks[0]]),\n",
        "                 arrowprops=dict(arrowstyle='<->', color='gray'))\n",
        "    plt.text((time_axis[systolic_peaks[0]] + time_axis[diastolic_peaks[0]]) / 2,\n",
        "             (ppg_signal_normalized[systolic_peaks[0]] + ppg_signal_normalized[diastolic_peaks[0]]) / 2,\n",
        "             f'Amplitude Diff\\n{amplitude_diff:.2f}', ha='center', color='gray')\n",
        "\n",
        "# Time Difference (Systolic to Dicrotic Notch)\n",
        "if len(systolic_peaks) > 0 and len(dicrotic_notches) > 0:\n",
        "    time_diff = time_axis[dicrotic_notches[0]] - time_axis[systolic_peaks[0]]\n",
        "    plt.annotate('', xy=(time_axis[systolic_peaks[0]], 0), xytext=(time_axis[dicrotic_notches[0]], 0),\n",
        "                 arrowprops=dict(arrowstyle='<->', color='orange'))\n",
        "    plt.text((time_axis[systolic_peaks[0]] + time_axis[dicrotic_notches[0]]) / 2, -0.05,\n",
        "             f'Time Diff\\n{time_diff:.2f}', ha='center', color='orange')\n",
        "\n",
        "# Add legend and labels\n",
        "plt.title(\"Annotated PPG Signal - Row 0\")\n",
        "plt.xlabel(\"Normalized Time\")\n",
        "plt.ylabel(\"Normalized Amplitude\")\n",
        "plt.legend()\n",
        "plt.grid(True)\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "8c68cda8-90aa-4f83-a552-a65fc6edb36a",
      "metadata": {
        "id": "8c68cda8-90aa-4f83-a552-a65fc6edb36a",
        "outputId": "8e223891-cd1d-40ca-b032-830adb4396ed"
      },
      "outputs": [
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from scipy.signal import savgol_filter, butter, filtfilt\n",
        "subset_data_normalized=pd.read_csv(\"subset_data_normalized.csv\")\n",
        "\n",
        "# Bandpass Filter Function\n",
        "def bandpass_filter(signal, lowcut, highcut, fs, order=4):\n",
        "    nyquist = 0.45 * fs\n",
        "    low = lowcut / nyquist\n",
        "    high = highcut / nyquist\n",
        "    b, a = butter(order, [low, high], btype='band')\n",
        "    filtered_signal = filtfilt(b, a, signal)\n",
        "    return filtered_signal\n",
        "\n",
        "# Adaptive Wavelet Denoising Function\n",
        "def adaptive_wavelet_denoising(signal, wavelet='coif5', level=2, threshold_method='soft'):\n",
        "    # Decompose the signal into wavelet coefficients\n",
        "    coeffs = pywt.wavedec(signal, wavelet, level=level)\n",
        "\n",
        "    # Calculate adaptive thresholds for each level\n",
        "    thresholded_coeffs = [coeffs[0]]  # Keep approximation coefficients\n",
        "    for i in range(1, len(coeffs)):\n",
        "        sigma = np.median(np.abs(coeffs[i])) / 0.6745  # Robust estimate of noise level\n",
        "        threshold = sigma * np.sqrt(2 * np.log(len(signal)))  # Adaptive threshold\n",
        "        thresholded_coeff = pywt.threshold(coeffs[i], threshold, mode=threshold_method)\n",
        "        thresholded_coeffs.append(thresholded_coeff)\n",
        "\n",
        "    # Reconstruct the signal from the thresholded coefficients\n",
        "    denoised_signal = pywt.waverec(thresholded_coeffs, wavelet)\n",
        "    return denoised_signal\n",
        "\n",
        "# Apply adaptive wavelet denoising to the PPG signal\n",
        "ppg_signal = subset_data_normalized.iloc[0, :-2].values  # Exclude the last two columns\n",
        "ppg_denoised = adaptive_wavelet_denoising(ppg_signal, wavelet='coif5', level=1, threshold_method='soft')\n",
        "\n",
        "# Apply Bandpass Filter to remove unwanted frequencies\n",
        "# Assume the signal is sampled at 100 Hz (fs = 100), adjust as needed\n",
        "fs = 140\n",
        "lowcut = 0.6  # Lower frequency in Hz\n",
        "highcut = 11.5  # Higher frequency in Hz\n",
        "ppg_filtered = bandpass_filter(ppg_denoised, lowcut, highcut, fs)\n",
        "\n",
        "# Apply Savitzky-Golay smoothing to the filtered signal\n",
        "ppg_smoothed = savgol_filter(ppg_filtered, window_length=31, polyorder=1)\n",
        "\n",
        "# Plotting the results\n",
        "plt.figure(figsize=(12, 6))\n",
        "plt.plot(ppg_smoothed, label='Final Smoothed Signal', color='red')\n",
        "plt.title('Adaptive Wavelet Denoising with Bandpass Filtering and Smoothing')\n",
        "plt.legend()\n",
        "plt.xlabel('Sample')\n",
        "plt.ylabel('Amplitude')\n",
        "plt.grid(True)\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "150d3cc4-6cd7-4ca0-a642-edb2e8ee2e92",
      "metadata": {
        "id": "150d3cc4-6cd7-4ca0-a642-edb2e8ee2e92",
        "outputId": "cddc83db-d037-4c9b-cfec-cd0e833238d6"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Feature extraction completed. The features have been saved to 'normalised_extracted_features.csv'.\n"
          ]
        }
      ],
      "source": [
        "from scipy.stats import skew, kurtosis, entropy\n",
        "\n",
        "# Load your dataset (assuming it is saved as a CSV file)\n",
        "df = pd.read_csv('subset_data_normalized.csv')\n",
        "\n",
        "# Assuming the first 874 columns are time-series data, and the last two columns are labels\n",
        "time_series_columns = df.columns[:-2]\n",
        "label_columns = df.columns[-2:]\n",
        "\n",
        "# Define a function to extract features from each row\n",
        "def extract_features(row):\n",
        "    signal = row[time_series_columns].values\n",
        "\n",
        "    # Systolic and Diastolic Amplitude\n",
        "    systolic_amplitude = np.max(signal)\n",
        "    diastolic_amplitude = np.min(signal)\n",
        "\n",
        "    # Augmentation Index (AIx)\n",
        "    first_peak = systolic_amplitude  # Approximate as the max value\n",
        "    second_peak = np.percentile(signal, 95)  # Second peak, approx as 95th percentile\n",
        "    augmentation_index = (second_peak - first_peak) / first_peak if first_peak != 0 else 0\n",
        "\n",
        "    # b/a Ratio\n",
        "    b_a_ratio = second_peak / first_peak if first_peak != 0 else 0\n",
        "\n",
        "    # Statistical Features\n",
        "    mean_val = np.mean(signal)\n",
        "    std_val = np.std(signal)\n",
        "    skewness = skew(signal)\n",
        "    kurt = kurtosis(signal)\n",
        "    signal_entropy = entropy(np.abs(signal))\n",
        "    rms = np.sqrt(np.mean(np.square(signal)))\n",
        "    peak_to_peak = systolic_amplitude - diastolic_amplitude\n",
        "    energy = np.sum(signal**2)\n",
        "\n",
        "    # Combine all features into a dictionary\n",
        "    features = {\n",
        "        'systolic_amplitude': systolic_amplitude,\n",
        "        'diastolic_amplitude': diastolic_amplitude,\n",
        "        'augmentation_index': augmentation_index,\n",
        "        'b_a_ratio': b_a_ratio,\n",
        "        'mean': mean_val,\n",
        "        'std_dev': std_val,\n",
        "        'skewness': skewness,\n",
        "        'kurtosis': kurt,\n",
        "        'entropy': signal_entropy,\n",
        "        'rms': rms,\n",
        "        'peak_to_peak': peak_to_peak,\n",
        "        'energy': energy,\n",
        "    }\n",
        "    return features\n",
        "\n",
        "# Apply the feature extraction to each row and create a new DataFrame\n",
        "features_df = df.apply(extract_features, axis=1, result_type='expand')\n",
        "\n",
        "# Include labels in the new DataFrame\n",
        "features_df[label_columns] = df[label_columns]\n",
        "\n",
        "# Save the extracted features to a new CSV file\n",
        "features_df.to_csv('normalised_extracted_features.csv', index=False)\n",
        "\n",
        "print(\"Feature extraction completed. The features have been saved to 'normalised_extracted_features.csv'.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "fa54b0b8-0010-4528-a928-2ac4c69ab0bc",
      "metadata": {
        "id": "fa54b0b8-0010-4528-a928-2ac4c69ab0bc"
      },
      "outputs": [],
      "source": [
        "normalised_extracted_features=pd.read_csv(\"normalised_extracted_features.csv\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "5cd5672d-c971-487f-a230-1c2cba4e97fb",
      "metadata": {
        "id": "5cd5672d-c971-487f-a230-1c2cba4e97fb",
        "outputId": "819ddcdf-8373-4fa8-94b5-cf1d2ac71438"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>systolic_amplitude</th>\n",
              "      <th>diastolic_amplitude</th>\n",
              "      <th>augmentation_index</th>\n",
              "      <th>b_a_ratio</th>\n",
              "      <th>mean</th>\n",
              "      <th>std_dev</th>\n",
              "      <th>skewness</th>\n",
              "      <th>kurtosis</th>\n",
              "      <th>entropy</th>\n",
              "      <th>rms</th>\n",
              "      <th>peak_to_peak</th>\n",
              "      <th>energy</th>\n",
              "      <th>873</th>\n",
              "      <th>874</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.757341</td>\n",
              "      <td>0.276152</td>\n",
              "      <td>-0.060786</td>\n",
              "      <td>0.939214</td>\n",
              "      <td>0.494284</td>\n",
              "      <td>0.125489</td>\n",
              "      <td>0.196503</td>\n",
              "      <td>-1.109900</td>\n",
              "      <td>6.739602</td>\n",
              "      <td>0.509965</td>\n",
              "      <td>0.481189</td>\n",
              "      <td>227.036097</td>\n",
              "      <td>0.373485</td>\n",
              "      <td>0.364558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.749446</td>\n",
              "      <td>0.236322</td>\n",
              "      <td>-0.093646</td>\n",
              "      <td>0.906354</td>\n",
              "      <td>0.495439</td>\n",
              "      <td>0.120367</td>\n",
              "      <td>-0.005270</td>\n",
              "      <td>-1.126107</td>\n",
              "      <td>6.741826</td>\n",
              "      <td>0.509851</td>\n",
              "      <td>0.513124</td>\n",
              "      <td>226.934441</td>\n",
              "      <td>0.653482</td>\n",
              "      <td>0.647596</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.813504</td>\n",
              "      <td>0.267257</td>\n",
              "      <td>-0.087618</td>\n",
              "      <td>0.912382</td>\n",
              "      <td>0.495239</td>\n",
              "      <td>0.133716</td>\n",
              "      <td>0.534041</td>\n",
              "      <td>-0.757738</td>\n",
              "      <td>6.736345</td>\n",
              "      <td>0.512973</td>\n",
              "      <td>0.546246</td>\n",
              "      <td>229.722435</td>\n",
              "      <td>0.452838</td>\n",
              "      <td>0.457110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.805717</td>\n",
              "      <td>0.229670</td>\n",
              "      <td>-0.125408</td>\n",
              "      <td>0.874592</td>\n",
              "      <td>0.494408</td>\n",
              "      <td>0.130989</td>\n",
              "      <td>0.055501</td>\n",
              "      <td>-0.906500</td>\n",
              "      <td>6.736105</td>\n",
              "      <td>0.511466</td>\n",
              "      <td>0.576047</td>\n",
              "      <td>228.374415</td>\n",
              "      <td>0.389374</td>\n",
              "      <td>0.383929</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.778903</td>\n",
              "      <td>0.255630</td>\n",
              "      <td>-0.069332</td>\n",
              "      <td>0.930668</td>\n",
              "      <td>0.494703</td>\n",
              "      <td>0.123376</td>\n",
              "      <td>0.629235</td>\n",
              "      <td>-0.659090</td>\n",
              "      <td>6.741791</td>\n",
              "      <td>0.509856</td>\n",
              "      <td>0.523273</td>\n",
              "      <td>226.938903</td>\n",
              "      <td>0.361350</td>\n",
              "      <td>0.348060</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   systolic_amplitude  diastolic_amplitude  augmentation_index  b_a_ratio  \\\n",
              "0            0.757341             0.276152           -0.060786   0.939214   \n",
              "1            0.749446             0.236322           -0.093646   0.906354   \n",
              "2            0.813504             0.267257           -0.087618   0.912382   \n",
              "3            0.805717             0.229670           -0.125408   0.874592   \n",
              "4            0.778903             0.255630           -0.069332   0.930668   \n",
              "\n",
              "       mean   std_dev  skewness  kurtosis   entropy       rms  peak_to_peak  \\\n",
              "0  0.494284  0.125489  0.196503 -1.109900  6.739602  0.509965      0.481189   \n",
              "1  0.495439  0.120367 -0.005270 -1.126107  6.741826  0.509851      0.513124   \n",
              "2  0.495239  0.133716  0.534041 -0.757738  6.736345  0.512973      0.546246   \n",
              "3  0.494408  0.130989  0.055501 -0.906500  6.736105  0.511466      0.576047   \n",
              "4  0.494703  0.123376  0.629235 -0.659090  6.741791  0.509856      0.523273   \n",
              "\n",
              "       energy       873       874  \n",
              "0  227.036097  0.373485  0.364558  \n",
              "1  226.934441  0.653482  0.647596  \n",
              "2  229.722435  0.452838  0.457110  \n",
              "3  228.374415  0.389374  0.383929  \n",
              "4  226.938903  0.361350  0.348060  "
            ]
          },
          "execution_count": 75,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "normalised_extracted_features.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4e84f84f-54f5-4abe-aa20-9b924b839df3",
      "metadata": {
        "id": "4e84f84f-54f5-4abe-aa20-9b924b839df3",
        "outputId": "3b9de648-1a50-44cc-a22e-8331d3f52285"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Min Value: -1.6305301837451138\n",
            "Max Value: 232.6337213816115\n"
          ]
        }
      ],
      "source": [
        "min_value = np.min(normalised_extracted_features)\n",
        "max_value = np.max(normalised_extracted_features)\n",
        "\n",
        "print(\"Min Value:\", min_value)\n",
        "print(\"Max Value:\", max_value)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "df18b7e6-3e0e-467c-a70e-86b83713695e",
      "metadata": {
        "id": "df18b7e6-3e0e-467c-a70e-86b83713695e"
      },
      "outputs": [],
      "source": [
        "normalised_extracted_features_final= normalised_extracted_features.apply(lambda x: (x - x.min()) / (x.max() - x.min()), axis=0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "53d09b6a-2af4-4d25-9ae2-7e9b66afb935",
      "metadata": {
        "id": "53d09b6a-2af4-4d25-9ae2-7e9b66afb935",
        "outputId": "b4dabbf6-4c75-4db5-af60-16599c360823"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Min Value: 0.0\n",
            "Max Value: 1.0\n"
          ]
        }
      ],
      "source": [
        "# Assuming 'data' is the numpy ndarray of your dataset\n",
        "min_value = np.min(normalised_extracted_features_final)\n",
        "max_value = np.max(normalised_extracted_features_final)\n",
        "\n",
        "print(\"Min Value:\", min_value)\n",
        "print(\"Max Value:\", max_value)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "41f36fad-9d5b-4fa1-b7a2-1d73977fc7a5",
      "metadata": {
        "id": "41f36fad-9d5b-4fa1-b7a2-1d73977fc7a5",
        "outputId": "b6979207-dc32-4055-e68a-e8252e4cdf5e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<bound method DataFrame.info of        systolic_amplitude  diastolic_amplitude  augmentation_index  b_a_ratio  \\\n",
              "0                0.221991             0.807825            0.914744   0.914744   \n",
              "1                0.196678             0.691310            0.814944   0.814944   \n",
              "2                0.402059             0.781804            0.833252   0.833252   \n",
              "3                0.377093             0.671850            0.718478   0.718478   \n",
              "4                0.291124             0.747791            0.888786   0.888786   \n",
              "...                   ...                  ...                 ...        ...   \n",
              "99995            0.263347             0.760196            0.807186   0.807186   \n",
              "99996            0.267546             0.631992            0.834706   0.834706   \n",
              "99997            0.218645             0.618274            0.882292   0.882292   \n",
              "99998            0.251175             0.704198            0.877109   0.877109   \n",
              "99999            0.269652             0.688030            0.815523   0.815523   \n",
              "\n",
              "       skewness  kurtosis   entropy       rms  peak_to_peak    energy  \\\n",
              "0      0.560877  0.030367  0.662186  0.355413      0.078853  0.353242   \n",
              "1      0.498935  0.028321  0.758099  0.343634      0.135553  0.341497   \n",
              "2      0.664497  0.074835  0.521716  0.665735      0.194362  0.663626   \n",
              "3      0.517591  0.056051  0.511354  0.510242      0.247273  0.507873   \n",
              "4      0.693720  0.087292  0.756573  0.344152      0.153573  0.342012   \n",
              "...         ...       ...       ...       ...           ...       ...   \n",
              "99995  0.532066  0.030995  0.639492  0.406361      0.130662  0.404075   \n",
              "99996  0.547352  0.058100  0.741588  0.312019      0.210801  0.309984   \n",
              "99997  0.530829  0.058036  0.736869  0.372139      0.192047  0.369924   \n",
              "99998  0.602665  0.061682  0.724666  0.431750      0.157910  0.429424   \n",
              "99999  0.526056  0.070500  0.718293  0.327733      0.177955  0.325645   \n",
              "\n",
              "            873       874  \n",
              "0      0.373485  0.364558  \n",
              "1      0.653482  0.647596  \n",
              "2      0.452838  0.457110  \n",
              "3      0.389374  0.383929  \n",
              "4      0.361350  0.348060  \n",
              "...         ...       ...  \n",
              "99995  0.376028  0.387582  \n",
              "99996  0.370288  0.363752  \n",
              "99997  0.390729  0.381525  \n",
              "99998  0.418229  0.415074  \n",
              "99999  0.363183  0.362505  \n",
              "\n",
              "[100000 rows x 12 columns]>"
            ]
          },
          "execution_count": 79,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df22=normalised_extracted_features_final.drop(columns=['mean','std_dev'])\n",
        "df22.info"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "baaa8a68-6c7b-4671-a600-a99d5ea8d622",
      "metadata": {
        "id": "baaa8a68-6c7b-4671-a600-a99d5ea8d622",
        "outputId": "c75c2f5c-6b17-43ee-db48-052d89112d1a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Systolic Prediction - Accuracy: 0.6864\n",
            "Diastolic Prediction - Accuracy: 0.6764\n",
            "Systolic Prediction - MSE: 0.0097, R²: 0.0386\n",
            "Diastolic Prediction - MSE: 0.0081, R²: 0.0550\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1400x600 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.svm import SVR\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.metrics import mean_squared_error, r2_score, accuracy_score\n",
        "\n",
        "# Load your dataset (df22)\n",
        "# Assuming df22 is already loaded\n",
        "# Take only 10,000 rows from the dataset\n",
        "df_subset = df22.sample(n=100000, random_state=42)  # Randomly select 10,000 rows\n",
        "\n",
        "# Split into features (X) and labels (y)\n",
        "X = df_subset.iloc[:, :-2]  # All columns except the last two\n",
        "y_systolic = df_subset.iloc[:, -2]  # Column '873'\n",
        "y_diastolic = df_subset.iloc[:, -1]  # Column '874'\n",
        "\n",
        "# Normalize the features\n",
        "scaler = StandardScaler()\n",
        "X_scaled = scaler.fit_transform(X)\n",
        "\n",
        "# Split the data into training and testing sets\n",
        "X_train, X_test, y_train_systolic, y_test_systolic = train_test_split(X_scaled, y_systolic, test_size=0.2, random_state=42)\n",
        "X_train, X_test, y_train_diastolic, y_test_diastolic = train_test_split(X_scaled, y_diastolic, test_size=0.2, random_state=42)\n",
        "\n",
        "# Train SVM models\n",
        "svm_systolic = SVR(kernel='rbf')  # Using Radial Basis Function (RBF) kernel\n",
        "svm_diastolic = SVR(kernel='rbf')\n",
        "\n",
        "svm_systolic.fit(X_train, y_train_systolic)\n",
        "svm_diastolic.fit(X_train, y_train_diastolic)\n",
        "\n",
        "# Predict on test set\n",
        "y_pred_systolic = svm_systolic.predict(X_test)\n",
        "y_pred_diastolic = svm_diastolic.predict(X_test)\n",
        "\n",
        "# Convert predictions to integer values for classification-like evaluation\n",
        "# This assumes discretized labels. If not, the accuracy score won't be meaningful.\n",
        "y_pred_systolic_discrete = np.round(y_pred_systolic)\n",
        "y_pred_diastolic_discrete = np.round(y_pred_diastolic)\n",
        "\n",
        "y_test_systolic_discrete = np.round(y_test_systolic)\n",
        "y_test_diastolic_discrete = np.round(y_test_diastolic)\n",
        "\n",
        "# Evaluate accuracy (discretized)\n",
        "accuracy_systolic = accuracy_score(y_test_systolic_discrete, y_pred_systolic_discrete)\n",
        "accuracy_diastolic = accuracy_score(y_test_diastolic_discrete, y_pred_diastolic_discrete)\n",
        "\n",
        "print(f\"Systolic Prediction - Accuracy: {accuracy_systolic:.4f}\")\n",
        "print(f\"Diastolic Prediction - Accuracy: {accuracy_diastolic:.4f}\")\n",
        "\n",
        "# Evaluate MSE and R² for continuous predictions\n",
        "mse_systolic = mean_squared_error(y_test_systolic, y_pred_systolic)\n",
        "mse_diastolic = mean_squared_error(y_test_diastolic, y_pred_diastolic)\n",
        "\n",
        "r2_systolic = r2_score(y_test_systolic, y_pred_systolic)\n",
        "r2_diastolic = r2_score(y_test_diastolic, y_pred_diastolic)\n",
        "\n",
        "print(f\"Systolic Prediction - MSE: {mse_systolic:.4f}, R²: {r2_systolic:.4f}\")\n",
        "print(f\"Diastolic Prediction - MSE: {mse_diastolic:.4f}, R²: {r2_diastolic:.4f}\")\n",
        "\n",
        "# Plot predictions vs actual values\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.figure(figsize=(14, 6))\n",
        "\n",
        "# Systolic\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.scatter(y_test_systolic, y_pred_systolic, alpha=0.6, color='blue', label='Predicted')\n",
        "plt.plot(y_test_systolic, y_test_systolic, color='red', label='Ideal Fit Line')\n",
        "plt.title('Systolic Prediction')\n",
        "plt.xlabel('Actual')\n",
        "plt.ylabel('Predicted')\n",
        "plt.legend()\n",
        "\n",
        "# Diastolic\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.scatter(y_test_diastolic, y_pred_diastolic, alpha=0.6, color='green', label='Predicted')\n",
        "plt.plot(y_test_diastolic, y_test_diastolic, color='red', label='Ideal Fit Line')\n",
        "plt.title('Diastolic Prediction')\n",
        "plt.xlabel('Actual')\n",
        "plt.ylabel('Predicted')\n",
        "plt.legend()\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "edaacfb3-15b3-40f7-8250-eb495c80d90b",
      "metadata": {
        "id": "edaacfb3-15b3-40f7-8250-eb495c80d90b",
        "outputId": "c5673cbc-755b-44f8-a8f2-5c1b75a98abb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Systolic Prediction - MSE: 0.009834746397642393 R²: -0.011762936617372821\n",
            "Diastolic Prediction - MSE: 0.007961656630707642 R²: 0.007714223200315895\n",
            "Explained Variance Ratio of PCA Components: [0.36332707 0.29800964 0.18644227 0.1092525  0.0360621  0.00538263]\n",
            "Systolic Prediction - Accuracy: 0.6864\n",
            "Diastolic Prediction - Accuracy: 0.6764\n"
          ]
        }
      ],
      "source": [
        "from sklearn.decomposition import PCA\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.svm import SVR\n",
        "from sklearn.metrics import mean_squared_error, r2_score, accuracy_score\n",
        "\n",
        "# Assuming df22 is your dataset\n",
        "# Take only 50,000 rows\n",
        "subset_data = normalised_extracted_features_final.iloc[:50000, :]\n",
        "\n",
        "# Separate features (X) and labels (y)\n",
        "X = subset_data.iloc[:, :-2].values  # All columns except the last two (labels)\n",
        "y_systolic = subset_data.iloc[:, -2].values  # Column 873\n",
        "y_diastolic = subset_data.iloc[:, -1].values  # Column 874\n",
        "\n",
        "# Apply PCA to reduce dimensionality\n",
        "n_components = 6 # Adjust the number of principal components as needed\n",
        "pca = PCA(n_components=n_components)\n",
        "X_pca = pca.fit_transform(X)\n",
        "\n",
        "# Split into train and test sets\n",
        "X_train, X_test, y_systolic_train, y_systolic_test = train_test_split(\n",
        "    X_pca, y_systolic, test_size=0.3, random_state=42\n",
        ")\n",
        "X_train, X_test, y_diastolic_train, y_diastolic_test = train_test_split(\n",
        "    X_pca, y_diastolic, test_size=0.3, random_state=42\n",
        ")\n",
        "\n",
        "# Train SVM for Systolic\n",
        "svm_systolic = SVR(kernel='rbf', C=5, gamma=0.1)\n",
        "svm_systolic.fit(X_train, y_systolic_train)\n",
        "\n",
        "# Predict and evaluate for Systolic\n",
        "y_systolic_pred = svm_systolic.predict(X_test)\n",
        "systolic_mse = mean_squared_error(y_systolic_test, y_systolic_pred)\n",
        "systolic_r2 = r2_score(y_systolic_test, y_systolic_pred)\n",
        "\n",
        "# Train SVM for Diastolic\n",
        "svm_diastolic = SVR(kernel='rbf', C=5, gamma=0.1)\n",
        "svm_diastolic.fit(X_train, y_diastolic_train)\n",
        "\n",
        "# Predict and evaluate for Diastolic\n",
        "y_diastolic_pred = svm_diastolic.predict(X_test)\n",
        "diastolic_mse = mean_squared_error(y_diastolic_test, y_diastolic_pred)\n",
        "diastolic_r2 = r2_score(y_diastolic_test, y_diastolic_pred)\n",
        "\n",
        "# Print results\n",
        "print(\"Systolic Prediction - MSE:\", systolic_mse, \"R²:\", systolic_r2)\n",
        "print(\"Diastolic Prediction - MSE:\", diastolic_mse, \"R²:\", diastolic_r2)\n",
        "\n",
        "# Explained variance by PCA components\n",
        "explained_variance = pca.explained_variance_ratio_\n",
        "print(\"Explained Variance Ratio of PCA Components:\", explained_variance)\n",
        "\n",
        "accuracy_systolic = accuracy_score(y_test_systolic_discrete, y_pred_systolic_discrete)\n",
        "accuracy_diastolic = accuracy_score(y_test_diastolic_discrete, y_pred_diastolic_discrete)\n",
        "\n",
        "print(f\"Systolic Prediction - Accuracy: {accuracy_systolic:.4f}\")\n",
        "print(f\"Diastolic Prediction - Accuracy: {accuracy_diastolic:.4f}\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "46a6f542-fe90-4c50-9cb1-cfde61be4f9f",
      "metadata": {
        "id": "46a6f542-fe90-4c50-9cb1-cfde61be4f9f"
      },
      "outputs": [],
      "source": [
        "# apply ridge on -1 to 1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "7015e1b9-1f6f-42dd-bfa2-681a0a52c181",
      "metadata": {
        "id": "7015e1b9-1f6f-42dd-bfa2-681a0a52c181"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.svm import SVR\n",
        "from sklearn.linear_model import Ridge, Lasso\n",
        "from sklearn.metrics import mean_squared_error, r2_score, accuracy_score"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a46633e3-99cf-4a93-a154-b60f9493b782",
      "metadata": {
        "id": "a46633e3-99cf-4a93-a154-b60f9493b782"
      },
      "outputs": [],
      "source": [
        "#KNN"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "183ab26a-0170-4a2a-ad04-ff97080f2bcd",
      "metadata": {
        "id": "183ab26a-0170-4a2a-ad04-ff97080f2bcd",
        "outputId": "3a0f5773-7025-4a7f-c62b-0157e3213a84"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Systolic Prediction:\n",
            "Best Params: {'metric': 'manhattan', 'n_neighbors': 46, 'weights': 'distance'}\n",
            "MSE: 0.0051, R²: 0.4762\n",
            "\n",
            "Diastolic Prediction:\n",
            "Best Params: {'metric': 'manhattan', 'n_neighbors': 53, 'weights': 'distance'}\n",
            "MSE: 0.0042, R²: 0.4841\n",
            "Explained Variance Ratio of PCA Components: [0.36332707 0.29800964 0.18644227 0.1092525  0.0360621  0.00538263\n",
            " 0.00138059]\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 1400x600 with 2 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from sklearn.model_selection import GridSearchCV\n",
        "from sklearn.neighbors import KNeighborsRegressor\n",
        "from sklearn.metrics import mean_squared_error, r2_score\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn.model_selection import train_test_split\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Assuming `normalised_extracted_features_final` is already defined\n",
        "subset_data = normalised_extracted_features_final.iloc[: 50000, :]\n",
        "\n",
        "# Separate features (X) and labels (y)\n",
        "X = subset_data.iloc[:, :-2].values  # All columns except the last two (labels)\n",
        "y_systolic = subset_data.iloc[:, -2].values  # Systolic (Column 873)\n",
        "y_diastolic = subset_data.iloc[:, -1].values  # Diastolic (Column 874)\n",
        "\n",
        "# Apply PCA to reduce dimensionality\n",
        "n_components = 7  # Adjust the number of principal components as needed\n",
        "pca = PCA(n_components=n_components)\n",
        "X_pca = pca.fit_transform(X)\n",
        "\n",
        "# Split into train and test sets\n",
        "X_train, X_test, y_systolic_train, y_systolic_test = train_test_split(\n",
        "    X_pca, y_systolic, test_size=0.2, random_state=42\n",
        ")\n",
        "X_train, X_test, y_diastolic_train, y_diastolic_test = train_test_split(\n",
        "    X_pca, y_diastolic, test_size=0.2, random_state=42\n",
        ")\n",
        "\n",
        "# Define hyperparameter grid for GridSearchCV\n",
        "param_grid = {\n",
        "    \"n_neighbors\": np.arange(1, 55),\n",
        "    \"weights\": [\"uniform\", \"distance\"],\n",
        "    \"metric\": [\"euclidean\", \"manhattan\", \"minkowski\"]\n",
        "}\n",
        "\n",
        "# Grid Search for Systolic Prediction (KNN Regression)\n",
        "knn_systolic = KNeighborsRegressor()\n",
        "grid_search_systolic = GridSearchCV(\n",
        "    estimator=knn_systolic,\n",
        "    param_grid=param_grid,\n",
        "    cv=4,\n",
        "    scoring=\"neg_mean_squared_error\",\n",
        "    n_jobs=-1\n",
        ")\n",
        "grid_search_systolic.fit(X_train, y_systolic_train)\n",
        "best_knn_systolic = grid_search_systolic.best_estimator_\n",
        "\n",
        "# Evaluate Systolic Prediction\n",
        "systolic_pred = best_knn_systolic.predict(X_test)\n",
        "systolic_mse = mean_squared_error(y_systolic_test, systolic_pred)\n",
        "systolic_r2 = r2_score(y_systolic_test, systolic_pred)\n",
        "\n",
        "# Grid Search for Diastolic Prediction (KNN Regression)\n",
        "knn_diastolic = KNeighborsRegressor()\n",
        "grid_search_diastolic = GridSearchCV(\n",
        "    estimator=knn_diastolic,\n",
        "    param_grid=param_grid,\n",
        "    cv=4,\n",
        "    scoring=\"neg_mean_squared_error\",\n",
        "    n_jobs=-1\n",
        ")\n",
        "grid_search_diastolic.fit(X_train, y_diastolic_train)\n",
        "best_knn_diastolic = grid_search_diastolic.best_estimator_\n",
        "\n",
        "# Evaluate Diastolic Prediction\n",
        "diastolic_pred = best_knn_diastolic.predict(X_test)\n",
        "diastolic_mse = mean_squared_error(y_diastolic_test, diastolic_pred)\n",
        "diastolic_r2 = r2_score(y_diastolic_test, diastolic_pred)\n",
        "\n",
        "# Print Results\n",
        "print(\"Systolic Prediction:\")\n",
        "print(\"Best Params:\", grid_search_systolic.best_params_)\n",
        "print(f\"MSE: {systolic_mse:.4f}, R²: {systolic_r2:.4f}\")\n",
        "\n",
        "print(\"\\nDiastolic Prediction:\")\n",
        "print(\"Best Params:\", grid_search_diastolic.best_params_)\n",
        "print(f\"MSE: {diastolic_mse:.4f}, R²: {diastolic_r2:.4f}\")\n",
        "\n",
        "# Explained variance by PCA components\n",
        "explained_variance = pca.explained_variance_ratio_\n",
        "print(\"Explained Variance Ratio of PCA Components:\", explained_variance)\n",
        "\n",
        "# Plot Results\n",
        "plt.figure(figsize=(14, 6))\n",
        "\n",
        "# Systolic Scatter Plot\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.scatter(y_systolic_test, systolic_pred, alpha=0.6, color='blue', label='Predicted')\n",
        "plt.plot(y_systolic_test, y_systolic_test, color='red', label='Ideal Fit Line')\n",
        "plt.title('Systolic Prediction')\n",
        "plt.xlabel('Actual')\n",
        "plt.ylabel('Predicted')\n",
        "plt.legend()\n",
        "\n",
        "# Diastolic Scatter Plot\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.scatter(y_diastolic_test, diastolic_pred, alpha=0.6, color='green', label='Predicted')\n",
        "plt.plot(y_diastolic_test, y_diastolic_test, color='red', label='Ideal Fit Line')\n",
        "plt.title('Diastolic Prediction')\n",
        "plt.xlabel('Actual')\n",
        "plt.ylabel('Predicted')\n",
        "plt.legend()\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "73365e76-cc4e-4bae-8016-82d8f238ccd9",
      "metadata": {
        "id": "73365e76-cc4e-4bae-8016-82d8f238ccd9"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "e695943b-5cc2-4181-a8ad-77fb42ff08fd",
      "metadata": {
        "id": "e695943b-5cc2-4181-a8ad-77fb42ff08fd"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ff232cd0-65f1-45c3-a5bd-a34d88a66983",
      "metadata": {
        "id": "ff232cd0-65f1-45c3-a5bd-a34d88a66983"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "c20a8e20-dbbe-4266-8bce-38d3737abdb4",
      "metadata": {
        "id": "c20a8e20-dbbe-4266-8bce-38d3737abdb4"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "08866986-4362-4526-b976-e3ff012789a5",
      "metadata": {
        "id": "08866986-4362-4526-b976-e3ff012789a5"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.12.7"
    },
    "colab": {
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}